Automatic sample and standard preparation based on recognition of sample identity and sample type

ABSTRACT

Systems and methods for managing a sample preparation and analysis system based on detected unique sample identities and locations is described. A method embodiment includes, but is not limited to, storing on a sample analysis information system a sample type and a sample type protocol for execution by a sample preparation system via a sample data manager; storing on the sample analysis information system an association between a unique identifier positioned on a sample container and the sample type with a sample logging manager; identifying the unique identifier at the sample preparation system with an identifier capture device of the sample preparation system; accessing from the sample analysis information system the sample type protocol based on the sample type associated with the unique identifier; and queuing a sampling procedure to execute the sample type protocol based on a sample order assigned to the sample type via the sample data manager.

CROSS-REFERENCE TO RELATED APPLICATIONS

The present application claims the benefit under 35 U.S.C. § 119(e) ofU.S. Provisional Application Ser. No. 62/738,527, filed Sep. 28, 2018,and titled “AUTOSAMPLER WITH AUTOMATIC SAMPLE AND STANDARD PREPARATIONBASED ON RECOGNITION OF SAMPLE IDENTITY.” U.S. Provisional ApplicationSer. No. 62/738,527 is herein incorporated by reference in its entirety.

BACKGROUND

In many laboratory settings, it is often necessary to analyze a largenumber of chemical or biochemical samples at one time. In order tostream-line such processes, the manipulation of samples has beenmechanized. Such mechanized sampling is commonly referred to asautosampling and is performed using an automated sampling device orautosampler.

SUMMARY

Systems and methods for managing a sample preparation and analysissystem based on detected unique sample identities and locations isdescribed. A method embodiment includes, but is not limited to, storingon a sample analysis information system a sample type and a sample typeprotocol for execution by a sample preparation system via a sample datamanager; storing on the sample analysis information system anassociation between a unique identifier positioned on a sample containerand the sample type with a sample logging manager; identifying theunique identifier at the sample preparation system with an identifiercapture device of the sample preparation system; accessing from thesample analysis information system the sample type protocol based on thesample type associated with the unique identifier; and queuing asampling procedure to execute the sample type protocol based on a sampleorder assigned to the sample type via the sample data manager.

This Summary is provided to introduce a selection of concepts in asimplified form that are further described below in the DetailedDescription. This Summary is not intended to identify key features oressential features of the claimed subject matter, nor is it intended tobe used as an aid in determining the scope of the claimed subjectmatter.

FIGURES

The Detailed Description is described with reference to the accompanyingfigures. The use of the same reference numbers in different instances inthe description and the figures may indicate similar or identical items.

FIG. 1 is a diagram of a sample preparation system network forautomatically identifying unique samples and applying a specified samplepreparation protocol based on the unique sample identity to queue andprepare samples and standards for analysis in accordance with exampleimplementations of the present disclosure.

FIG. 2 is an illustration of an example user interface of a sample datamanager in accordance with example implementations of the presentdisclosure.

FIG. 3 is a view of a scanner of a sample logging manager to recordinformation associated with a unique identity of a sample container withthe sample analysis information system in accordance with exampleimplementations of the present disclosure.

FIG. 4 is an isometric view of example sample containers having uniqueidentifiers to be scanned by the sample logging manager and samplepreparation system.

FIG. 5 is an illustration of an example user interface of a samplelogging manager in accordance with example implementations of thepresent disclosure.

FIG. 6 is an isometric view of a sample preparation system having a massbalance to measure a weight of a sample and facilitate providing aspecified weight boundary to prepare a sample by weight in accordancewith example implementations of the present disclosure.

FIG. 7A is an isometric view of example sample containers positioned insample racks or holders at the sample preparation system.

FIG. 7B is an isometric view of a sample preparation system having anidentifier capture device to scan unique identifiers on samplecontainers in accordance with example implementations of the presentdisclosure.

FIG. 7C is an isometric view of a sample preparation system having anidentifier capture device to scan unique identifiers on samplecontainers held by a sample rack in accordance with exampleimplementations of the present disclosure.

FIG. 8 is an isometric view of an identifier arm assembly of the samplepreparation system having an identifier capture device.

FIG. 9A is an illustration of a user interface of the sample preparationsystem showing sample containers received in positions 1 through 6 of asample holder.

FIG. 9B is an illustration of the sample preparation system undergoing adiscover operation to scan the unique identifiers on sample containersand a user interface of the sample preparation system following scanningin accordance with example implementations of the present disclosure.

FIG. 10 is an illustration of an example user interface of the sampleanalysis information system showing a sample queue assigned according tosample types identified by the sample preparation system in accordancewith example implementations of the present disclosure.

FIG. 11 is an illustration of an example user interface of the sampleanalysis information system showing example concentration data ofvarious elements in accordance with example implementations of thepresent disclosure.

FIG. 12 is a flow diagram of a method for managing data associated withsample preparation and analysis in accordance with exampleimplementations of the present disclosure.

FIG. 13 is a flow diagram of a method for managing data associated withsample preparation and analysis in accordance with exampleimplementations of the present disclosure.

DETAILED DESCRIPTION Overview

Often in laboratory or industry settings, large numbers of samples areanalyzed. Autosamplers are frequently used to gather and introducesamples for subsequent testing of the composition of these samples.Using an autosampler typically allows more samples and other solutionsto be prepared and tested as compared to manual preparation methods.During the sample preparation process, multiple containers may be usedto prepare samples, prepare standards (e.g., to generate one or morecalibration curves), introduce standard spikes to a sample, hold variousreagents, hold samples, or the like. Determination of trace elementalconcentrations or amounts in a sample can provide an indication ofpurity of the sample, or an acceptability of the sample for use as areagent, reactive component, or the like. For instance, in certainproduction or manufacturing processes (e.g., mining, metallurgy,semiconductor fabrication, pharmaceutical processing, etc.), thetolerances for impurities can be very strict, for example, on the orderof fractions of parts per billion. For example, semiconductor processescan require ultralow detection limits for impurities in processchemicals including, but not limited to, ultrapure water (UPW) forwashing wafers, isopropyl alcohol (IPA) for drying wafers, hydrogenperoxide (H₂O₂), ammonia solution (NH₄OH), and the like. Failure todetect ultralow concentrations of impurities in such process chemicalscan ruin a semiconductor wafer, such as by precipitating such impuritiesout of solution and onto the wafer (e.g., depositing a metallic impurityor other conductivity hazard onto the wafer, such as throughprecipitation of the impurity out of solution, the wafer acting as aconcentrator surface for the impurity, or the like).

The ordering of the various containers available to an autosampler canaffect the accuracy of data generated from analysis of the samplescontained therein. For instance, autosampling systems can rely on aspecific or predetermined arrangement of sample containers held within asample rack while the probe is introduced to each sample container in aserial manner. Results of the analysis of the samples are then tied tothe specific or predetermined arrangement following the serialprogression. As such, the results of such analysis can be erroneous ifan individual deviates from the specific or predetermined arrangementwhen placing sample containers in the sample rack(s). The risk of errorcan increase if the individual at the autosampler differs from theindividual handling the initial gathering of the sample. For instance,mislabeling or misidentifying a sample during or after transit from asampling point can cause information associated with the sample to beerroneously associated with another sample, such as through misplacementof the sample container within the sample rack, misplacement of a samplewithin a particular sample container, or the like.

Further, an individual can implement an incorrect sample preparationprotocol or sample analysis protocol for a particular sample, even whenthe sample is appropriately identified. For instance, the individual canutilize an incorrect calibration protocol, an incorrect dilution factor,introduce an incorrect fluid to the sample, fail to separate a sampleinto a sufficient number of sample replicates, or the like for a sample,thereby affecting the usefulness of the results of analysis of thesample. This risk increases as the number of individuals performing thesample preparation increases, which can be problematic for laboratoriesor industries as training and oversight costs increase. Still further,the particular ordering of samples handled by a sample preparationsystem can contribute to the performance of a system. For example,incomplete washout of sample between different sample types can lead toa chemical reaction within fluid lines of the system, leading to skewedanalytical results or even instrument damage (e.g., testing a baseimmediately prior to testing a strong acid).

Accordingly, a system for managing a sample preparation and analysissystem is described having integrated informational systems toautomatically identify unique samples and apply a specified analyticalprotocol based on the unique sample identity to queue and preparesamples and standards for analysis. A system embodiment includes asample analysis information system in communication with each of asample data manager, a sample logging manager, a sample preparationsystem, and a sample analysis system.

In example implementations, the sample data manager provides anindividual with a user interface to set sample handling protocols fordifferent sample types (or groups, classes, etc.) that are desired foranalysis by an analytic device, such as inductively coupled plasmaspectrometry instrumentation (e.g., an ICP mass spectrometer (ICPMS), anICP atomic emission spectrometer (ICPAES), etc. For example, a firstsample type can include a first acid (e.g., sulfuric acid— H₂SO₄), asecond sample type can include a peroxide (e.g., hydrogen peroxide—H₂O₂), a third sample type can include a second acid (e.g., nitric acid—HNO₃), and so forth, each with the ability to have differing samplehandling protocols unique to the sample type. When a sample is presentedfor analysis, the specific sample handling protocol set via the sampledata manager is automatically executed by the sample preparation systemwhich can initiate the sample handling protocols through communicationwith the sample analysis information system upon identification of asample identity of the sample presented for analysis or upon selectionof the sample type to be associated with the sample in a particularsample container.

The sample identity is assigned to a sample in a sample containerthrough user interface with the sample logging manager. For example,with the sample logging manager, a user scans an identifier (e.g., a barcode, a 2-D bar code, etc.) positioned on a sample container and inputsinformation in the sample logging manager associated with the samplecontainer including, but not limited to, an identity of the userinteracting with the sample logging manager (e.g., via a unique login),a date of sample data entry, a time of sample data entry, a source ofthe sample (e.g., sampling point within a facility, a customer source,etc.), comments associated with the sample, or the like. The labeledsample containers can be placed in a sample rack or on a sampling deckof the sample preparation system without a specific arrangement of thecontainers with respect to each other. In implementations, the samplepreparation system dynamically scans for the presence of the labeledsample containers during a discovery operation and arranges samplepreparation of the samples within the containers based on compiling theinformation associated with the samples entered via the sample loggingmanager and the sample type protocols entered via the sample datamanager through communication with the sample analysis informationsystem. The sample preparation system queues and processes samplesaccording to the identified sample types, where the locations of thesample within the sample racks dictates the positioning of the sampleprobe during the queuing rather than a static serial progression throughthe rack positions.

Example Implementations

Referring to FIGS. 1 through 13 a system 100 for managing a samplepreparation and analysis system is shown in accordance with exampleimplementations of the present disclosure. The system 100 generallyincludes a sample preparation system network for automaticallyidentifying unique samples and applying a specified analytical protocolbased on the unique sample identity to prepare samples and standards foranalysis and to queue the handling of the samples. With reference toFIG. 1, the system 100 is shown including a sample analysis informationsystem 102 communicatively connected with each of a sample data manager104, a sample logging manager 106, a sample preparation system 108, anda sample analysis system 110. In general, the sample data manager 104provides a platform to view data and edit protocols associated withsample preparation and analysis of samples handled by the system 100 viacommunication with the sample analysis information system 102, thesample logging manager 106 provides a platform to associate a fluidsample with a specific sample container based on a unique sampleidentifier positioned on a sample container and to assign a sample typeto the sample in the specific sample container, the sample preparationsystem 108 provides a platform to execute a sample protocol associatedwith the given sample type (e.g., to dilute the sample, divide a sampleinto multiple containers, add fluids or reagents to the sample, providea specified weight boundary to prepare a sample by weight, prepare anumber of calibration analyses, and the like), and the sample analysissystem 110 receives a sample from one or more sample preparation systems108 for analytic determination of one or more components present in thesample. The sample analysis system 110 is coupled to the samplepreparation system 108 to receive a fluid sample for analyticdetermination of one or more elements contained therein and can include,but is not limited to, inductively coupled plasma spectrometryinstrumentation, such as an ICP mass spectrometer (ICPMS), an ICP atomicemission spectrometer (ICPAES), etc.

In implementations, the sample preparation system 108 includes a samplelogging manager 106 to associate a sample type with a sample containerat the sample preparation system 108 (e.g., by scanning a sampleidentifier positioned on a sample container and/or on a sample holder).The sample preparation system 108 can include, for example, one or moreof a mass balance (e.g., described with reference to FIG. 6), a sampleprobe to remove fluids from a sample container and add fluids to asample container (e.g., for offline sample preparation), an inlinedilution system (e.g., for automated inline sample dilution andcalibration standard preparation), and the like. In implementations, thesample preparation system 108 includes a sample probe in fluidcommunication with an inline sample dilution system to receive thesample from the sample probe and prepare the sample for analysis by thesample analysis system 110, such as by introducing a diluent, astandard, a spike fluid, or combinations thereof, inline to the sampleaccording to one or more sample preparation protocols established by thesample data manager 104 and associated with a particular sample via thesample logging manager 106. For example, the sample preparation system108 can include one or more of a variable inline dilution systemdescribed in U.S. patent application Ser. No. 13/656,972 incorporatedherein by reference, an inline dilution and autocalibration systemdescribed in U.S. patent application Ser. No. 15/368,803 incorporatedherein by reference, a system for inline sample dilution described inU.S. patent application Ser. No. 16/119,228 incorporated herein byreference, or components or combinations thereof.

In implementations, the sample analysis information system 102 includesa database (e.g., a structured query language (SQL) database)communicatively connected with each of the sample data manager 104, thesample logging manager 106, the sample preparation system 108, and thesample analysis system 110 via one or more networks. The sample analysisinformation system 102 can also be communicatively connected with alaboratory information management system (LIMS), one or more clientdevices (e.g., mobile computing device), and the like to receive ortransmit data for managing sample preparation. The networks can includea variety of different communication pathways and network connectionswhich may be employed, individually or in combinations, to communicateamong the components of the system 100. Thus, the one or more networksmay be representative of communication pathways achieved using a singlenetwork or multiple networks. Further, the one or more networks arerepresentative of a variety of different types of networks andconnections that are contemplated including, but not necessarily limitedto: the Internet; an intranet; a Personal Area Network (PAN); a LocalArea Network (LAN) (e.g., Ethernet); a Wide Area Network (WAN); asatellite network; a cellular network; a mobile data network; wiredand/or wireless connections; and so forth. Examples of wireless networksinclude, but are not necessarily limited to: networks configured forcommunications according to: one or more standard of the Institute ofElectrical and Electronics Engineers (IEEE), such as 802.11 or 802.16(Wi-Max) standards; Wi-Fi standards promulgated by the Wi-Fi Alliance;Bluetooth standards promulgated by the Bluetooth Special Interest Group;and so on. Wired communications are also contemplated such as throughUniversal Serial Bus (USB), Ethernet, serial connections, and so forth.

The sample analysis information system 102 hosts or otherwise storesinformation associated with sample type analysis protocols, sample name,sample type, dilution method, dilution factor, standard type, samplehandling protocol, calibration type, sample order, number of calibrationpoints, wash method, logistic information associated with a givensample, and the like. Such sample information can be entered, modified,or removed through interaction of an individual with a user interfaceassociated with one or more of the sample data manager 104, the samplelogging manager 106, and the sample preparation system 108, orautomatically from the sample data manager 104, the sample loggingmanager 106, or the sample preparation system 108, for example, toimplement the appropriate sample preparation or analysis protocols for aspecific sample or samples. Access to each of the sample analysisinformation system 102, the sample data manager 104, the sample loggingmanager 106, and the sample preparation system 108 can be restrictedbased on user security or access credentials. For example, a user, suchas a laboratory technician tasked with gathering a sample may have alogin credential with security access to the sample logging manager 106and the sample preparation system 108, but with insufficient securitycredentials to access the sample data manager 104. Another individual,such as a laboratory manager tasked with overseeing the consistency oflaboratory sampling and processing may have a login credential withsecurity access to each the sample data manager 104, the sample loggingmanager 106, and the sample preparation system 108.

Sample Data Manager

The sample data manager 104 provides an interface for an individual toview data and edit protocols associated with sample preparation andanalysis of samples handled by the system 100. An example user interfaceof the sample data manager 104 is shown with reference to FIG. 2. Thesample data manager 104 permits a user (e.g., a lab manager) tointroduce specific sample type protocols into the system 100, such thatassignment of a sample type to a sample container or identification of asample of the specific sample type at the sample preparation system 108will cause the sample preparation system 108 to automatically executethe sample type protocol for that sample. In implementations, the system100 requires that a user have modification authority to add or modifyspecific sample type protocols via the sample data manager 104, whichcan ensure that consistent protocols are utilized by the system 100 toprepare samples for analysis by the sample analysis system 110. A sampletype protocol can include, but is not limited to, a specified samplepreparation method, a standard type, an analysis protocol, a sampleorder, a calibration type, a number of calibration points, a dilutionfactor associated with each calibration point, a wash method,preparation method, target sample weights or volumes, and the like.

The sample type protocol or portions thereof to be executed by thesample preparation system 108 can depend on the hardware of the samplepreparation system 108 at which a sample container is located. Forexample, when the sample preparation system 108 includes a mass balance(e.g., shown in FIG. 7A), the sample preparation system 108 can executeportions of the sample type protocol associated with target sampleweights. As another example, when the sample preparation system 108includes an autosampler with a sample probe to move fluids betweencontainers (e.g., shown in FIGS. 7B and 7C), the example preparationsystem 108 can execute portions of the sample type protocol associatedwith offline sample preparation including, but not limited to, movingsample into multiple sample containers for replicates, adding fluids toa sample (e.g., acid addition for sample digestion), diluting sample,and the like. As a further example, when the sample preparation system108 is fluidically coupled to the sample analysis system 110, theexample preparation system 108 can execute portions of the sample typeprotocol associated with preparation of standard solutions to buildcalibration curves, inline standard spikes, inline dilution, and thelike. The specified sample preparation method can include factorsassociated with a script used by the sample preparation system 108 tocoordinate operations of pumps and valves to facilitate the desiredtransfer, dilution, standard introduction, and handling of a fluidsample for analysis by the sample analysis system 110. The specifiedsample preparation method can include a sample size that is associatedwith a sample loop or sample holding line of the sample preparationsystem 108. The analysis protocol can include, but is not limited to, alist of which analytes that should be analyzed by the sample analysissystem 110, calibration levels for each standard calibration (e.g.,standard 1 for a selected element is 1 ppt, standard 2 for the selectedelement is 2 ppt, standard 3 for the selected element is 5 ppt, standard4 for the selected element is 10 ppt, etc.), dilution factors for eachstandard calibration, and the like. In implementations, only the dataassociated with the analytes identified in the analysis protocol ispopulated in the sample analysis information system 102 from resultsdetermined by the sample analysis system 110, even if the sampleanalysis system 110 generates data for elements not in the analysisprotocol for a given sample type. The sample analysis system 102 canstore information associated with data for elements not in the analysisprotocol for later review or review by a subset of users of the system100 (e.g., those with modification authority within the system 100).

The sample order of the sample type protocol provides a relative orderof handling a given sample type by the sample preparation system 108 ascompared to another sample type. For example, a sample type ofhydrochloric acid can have a sample order assigned in the sample datamanager 104 of 3, whereas a sample type of hydrogen peroxide can have asample order assigned in the sample data manager 104 of 2, and a sampletype of hydrogen fluoride can have a sample order assigned in the sampledata manager 104 of 1. Thus, if the sample preparation system 108 hassamples having a sample type assigned via the sample logging manager 106as hydrogen peroxide and samples having a sample type assigned via thesample logging manager 106 as hydrochloric acid for processing, thesample preparation system 108 will handle the hydrogen peroxide samplesprior to handling the hydrochloric acid samples due to the lower sampleorder assigned to the hydrogen peroxide samples. The sample orderprovides a user-defined ordering of samples with respect to othersamples to enhance performance of the system 100, such as by avoiding ormitigating chemical reactions within system fluid lines if incompletewashout of sample occurs. Generation of a sample queue based on sampletype to be handled by the sample preparation system 108 is discussedfurther herein with respect to FIGS. 9A and 9B.

The calibration type of the sample type protocol designates how often acalibration curve is built, whether an offline standard dilution (e.g.,using the sample probe to dispense a standard and diluent togetherwithin a container) or an inline standard dilution or addition (e.g., anMSA standard) is performed by the sample preparation system 108, and thelike. In implementations the calibration type is one of an externalcalibration type, an MSA calibration type, or an addition calibrationtype. The external calibration type directs the sample preparationsystem 108 to prepare a single calibration curve followed by analysis ofall samples queued for analysis. The MSA calibration type directs thesample preparation system 108 to prepare a separate calibration curvefor each individual sample queued for analysis. The addition calibrationtype directs the sample preparation system 108 to prepare a separatecalibration curve for each sample type of samples queued for analysis(i.e., a first calibration curve for all samples having a first sampletype, a second calibration curve for all samples having a second sampletype, etc.). The number of calibration points of the sample typeprotocol designates how many standard points are measured to build thestandard calibration curve, where dilution factors for each point can beset. For instance, a first calibration point is obtained throughanalysis by the sample analysis system 110 of a standard at a firstdilution factor, a second calibration point is obtained through analysisby the sample analysis system 110 of the standard at a second dilutionfactor, and so on for each calibration point associated with the sampletype protocol.

The wash method of the sample type protocol designates a script used bythe sample preparation system 108 to coordinate operations of pumps andvalves to facilitate the desired wash protocol (e.g., volume of rinsefluid, time of rinse, number of rinses, type of rinse fluid(s), etc.),where different sample types can have different wash methods. Thepreparation method provides customizable protocols for samplepreparation, such as offline autodilution or addition of fluids to asample, preparation of sample replicates by moving fluid from a firstsample container to one or more additional sample containers, and thelike. For instance, the sample preparation system 108 can execute thepreparation method of the sample type protocol to control a sample probeof the sample preparation system 108 or a separate autosampler todispense a sample/standard and diluent or other fluid together within acontainer. Alternatively or additionally, the preparation method caninclude inline dilution or fluid addition. Target sample weights orvolumes refers to syringe control of the sample probe 114 to take aparticular volume of sample, such as a solid sample suspended insolution or a sample having a particular density to draw consistentamounts for analysis between samples. For sample protocols involvingsample weights, the target sample weight can provide a specified weightboundary (e.g., a minimum target weight and a maximum target weight) fora particular sample type.

Sample Logging Manager

The sample logging manager 106 provides an interface for an individual(e.g., a lab technician) to associate a fluid sample with a specificsample container based on a unique sample identifier positioned on asample container. Referring to FIG. 3, the sample logging manager 106can include a bar code scanner 300, optical device, or other recognitiondevice to scan a sample identifier 302 positioned on a sample container304. For example, a user can enter via a computing device 306information associated with the sample to have the informationassociated with the sample identifier 302 via the sample logging manager106 to be stored at the sample analysis information system 102.Alternatively or additionally, the sample logging manager 106 isincluded in one or more sample preparation systems 108 to permit anindividual to select a particular sample type to be associated with aspecific sample container (e.g., via the sample identifier 302). Forexample, the sample preparation system 108 can include a scannerintegrated in a mass balance to scan the unique identifier 302 on thesample container 304 placed on the mass balance, where the mass balancecommunicates with the sample analysis information system 102 to identifythe sample type previously assigned to the sample container 304 or toassign a sample type to the sample container 304 is no sample type waspreviously assigned. As another example, the sample preparation system108 can include a scanner (e.g., identifier capture device 708 describedherein) to facilitate logging of sample information via the samplelogging manager 106 when sample containers 304 are positioned on a deckof an autosampler table for offline sample preparation or inline samplepreparation for analysis.

In implementations, the sample identifier 302 is unique to the specificsample container 304, such that different sample containers 304 havedifferent sample identifiers 302. The sample identifier 302 can includea one dimensional barcode or a data matrix two-dimensional (2D) barcode,such as a 12×12 matrix, a 13×13 matrix, a 14×14 matrix, or any othersuitable matrix. While square matrices are provided as example datamatrix barcodes, it is contemplated that rectangular matrices also maybe utilized. The sample identifier 302 can include other identificationindicia including, but not limited to: characters and/or patternsconfigured for recognition by an optical camera or sensor; radiofrequency identification (RFID) tags; raised surfaces for recognition bytouch sensors, optical sensors, and the like; illumination sourcesconfigured to generate a particular color (or wavelength), pattern oflight, etc.; other identification indicia configured for recognition byan identifier capture device of the sample preparation system 108; andso forth. Example sample containers 304 are provided in FIGS. 3 and 4.

A sample container 304 can include a plurality of sample identifiers302, which can be of the same or different type with respect to eachother. For example, referring to FIG. 3, the sample container 304 isshown with a first container identifier 302A and a second containeridentifier 302B, with a cap 308 having a third container identifier302C. The first container identifier 302A is shown as a data matrixtwo-dimensional barcode, whereas the second container identifier 302B isshown as a one-dimensional barcode. Each of the first containeridentifier 302A and the second container identifier 302B can uniquelyidentify the sample container 304 and can permit multiple scanningdevices to identify the sample container 304. For example, the firstcontainer identifier 302A can be accessible to and identified by theidentifier capture device of the sample preparation device 208 describedherein, and the second container identifier 302B can be accessible toand identified by the bar code scanner 300 or other scanner available ina lab or in the field. The third container identifier 302C on the cap308 can uniquely identify the cap 308 with respect to any other cap orwith respect to any container or container body. As such, dataassociated with the cap 308 (e.g., a contaminate level or contaminatehistory) can be tracked via the third container identifier 302Cindependently of data associated with the sample container 304 or sampleheld or previously held within the sample container 304 on which the cap308 is located or previously located.

A user can input information associated with a sample via the samplelogging manager 106 (e.g., via computing device 304, via a computingdevice communicatively connected with a sample preparation system 108, amobile computing device, or other terminal) following scanning of thesample identifier 302, where such data is stored at the sample analysisinformation system 102 for later retrieval to facilitate execution ofsample type protocols and sample queuing at the sample preparationdevice 108. An example user interface of the sample logging manager 106is shown with reference to FIG. 5. In implementations, the user canselect a sample type from a list of pre-entered sample types enteredinto the system 100 via the sample data manager 104, where the sampletype is then associated with the unique sample identifier 302 throughoutthe system 100 through communication coupling between the components ofthe system 100 with the sample analysis information system 102. Thesample logging manager 106 can also facilitate entering of additionalinformation to be associated with the unique identifier 302 including,but not limited to, an identity of the user interacting with the samplelogging manager 106 (e.g., via a unique login), a date of sample dataentry, a time of sample data entry, a source of the sample (e.g.,sampling point within a facility, a customer source, etc.), commentsassociated with the sample, or the like.

The sample logging manager 106 automatically associates a sample typeprotocol with the unique identifier 302 based on the sample typeselected by the user to provide the appropriate protocols to the samplepreparation system 108 without further interaction from the userinterfacing with the sample logging manager 106. Since the sample datamanager 104 manages the sample types and sample type protocolsindependently from the sample logging manager 106, the sample types andsample type protocols can be managed and monitored to provide consistentprotocols to be used throughout a facility or group of facilities forchemical analysis. For example, a lab manager, technical manager, orgroup of individuals can establish common protocols for use throughout afacility or group of facilities, independent of the number ofindividuals who obtain the samples for analysis. As such, hundreds ofsamples and more can be processed by the system 100 with appropriate andconsistent sample protocols for preparation of the samples by the samplepreparation system 108 and analysis of the samples by the sampleanalysis system 110. Accordingly, the sample type protocols can bemanaged through the sample data manager 104 for consistency betweensamples having the same sample type, as opposed to relying on additionaldata entry related to sample type protocols (independent of selectingthe sample type via the sample logging manager 106) during the gatheringof samples or introducing the samples to an autosampling device.

Sample Preparation System

Samples located at the sample preparation system 108 can be scanned todetermine whether a unique identifier 302 is located on the samplecontainer 304 or whether a unique identifier 302 present on the samplecontainer 304 is associated with a sample type (i.e., previously enteredvia the sample logging manager 106). If no unique identifier 302 ispresent or if no sample type is already associated with a uniqueidentifier 302 that is present, the sample logging manager 106 can beutilized to assign a sample type to the sample container 304 at thesample preparation system 108. The sample preparation system 108 caninclude, for example, one or more of a mass balance, a sample probe toremove fluids from a sample container and add fluids to a samplecontainer (e.g., for offline sample preparation), an inline dilutionsystem (e.g., for automated inline sample dilution and calibrationstandard preparation), and the like.

Referring to FIG. 6, the sample preparation system 108 is shown toinclude a mass balance 500 having a surface 502 to support a samplecontainer 304 for weighing the sample container 304 and any samplepresent therein. The mass balance 500 includes a scanner to recognizethe sample identifier 302 positioned on the sample containers 304 (e.g.,on a bottom surface of the sample container 304). The scanner caninclude, for example, one or more of a barcode scanner, an RFID reader,a camera, an optical detector, or the like. For example, the massbalance 500 can include a housing 504 beneath the surface 502 to housethe scanner oriented to scan through the surface 502 to detect sampleidentifiers 302 positioned on the surface 502. In implementations, thesurface 502 includes a light transmissive material to permit detectionof the sample identifiers 302 by the scanner through the surface 502. Inimplementations, the mass balance 500 is communicatively connected tothe sample analysis information system 102 to determine whether a sampleidentifier 302 detected by the mass balance 500 is associated with asample type. For instance, if a user previously associated a sample typewith the unique sample identifier 302 in the sample container 304, themass balance can access the appropriate sample type protocol establishedfor the sample type via the sample data manager 104. The sample typeprotocol for the mass balance 500 can include a minimum target weight ofsample and a maximum target weight of sample. For example, the samplecontainer 304 can be placed on the surface 502, where a tare function ofthe mass balance 500 can zero the weight of the sample container 304. Adisplay (e.g., display 506 on the mass balance 500, a display of acomputing device communicatively coupled with the mass balanced 500, orcombinations thereof) can show the current weight of sample in thesample container 304 as sample is introduced to the sample container304. The mass balance can compare the current weight of sample to theminimum target weight and maximum target weight assigned by the sampletype associated with the unique identifier 302. In implementations, thedisplay shows the current weight of sample held on the mass balance 500in a first format when the current weight is below the minimum weight ofsample or above the maximum weight of sample and shows the currentweight of sample held on the mass balance 500 in a second format whenthe current weight is at the minimum weight of sample, between theminimum weight of sample and the maximum weight of sample, or at themaximum weight of sample, responsive to execution of the sample typeprotocol. For example, when the current weight is outside of the minimumweight or maximum weight, the display can show the current weight in afirst color, size, or font (e.g., red color), and when the currentweight is at the minimum weight, at the maximum weight, or between theminimum weight and maximum weight, the display can show the currentweight in a second color, size, or font (e.g., green color).

Referring to FIG. 7A, example sample holders 600 are shown holdingsample containers 304 at the sample preparation system 108 for access bya sample probe supported by support 602. For instance, example samplepreparation systems 108 are shown in FIGS. 7B and 7C includingidentifier capture devices to scan the unique sample identifiers 302positioned on the sample containers 304 for recognition of types andlocations of samples present at the sample preparation system 108. Thesample preparation system 108 includes a probe arm assembly 700 coupledto the support 602 to support a sample probe 702 into which a sample orother fluid can be drawn from the sample containers 304 and into tubing704 or introduced to the sample container 304 through the sample probe702 (e.g., through pump action, through fluid communication with avacuum source, or the like). The tubing 704 is coupled to other portionsof the sample preparation system 108 to facilitate inline dilution,standard addition, and the like. The support 602 and position of theprobe arm assembly 700 are controlled by a motor (not shown), whichpermits translation of the support 602 through a center slot 706. Anidentifier capture device 708 is coupled to the support 602 via anidentifier arm assembly 710 to permit the identifier capture device 708to pass beneath a raised surface 712 on which the sample containers 304are positioned. The identifier capture device 708 passes underneath theraised surface 712 to provide access to the underside of the samplevessels 304 and associated sample identifiers 302. For example, as shownin FIG. 7B, the sample holder 600 can be positioned on the raisedsurface 712, where the identifier capture device 708 passes underneathto scan the sample identifiers 302 positioned on a bottom surface of thesample containers 304 held in the sample holder 600. The raised surface712 can define gaps 714 in the surface over which the sample holder 600and/or sample containers 604 are situated. In this manner, the sampleidentifiers 302 at the base or bottom of the sample containers 304 areaccessible to the identifier capture device 708 when positioned beneaththe raised surface 712. Alternatively, the raised surface 712, or aportion thereof, may be constructed from a substantially clear, lighttransmissive, or transparent material to expose the bottom portion ofthe sample containers 304 to the identifier capture device 708.Additionally or alternatively, the identifier capture device 708 oradditional identifier capture device can be positioned above the raisedsurface 712 (e.g., mounted to the probe arm assembly 700).

The identifier capture device 708 is configured to capture, image, orotherwise recognize the sample identifier 302 as the identifier armassembly 710 moves the identifier capture device 708 underneath thesample containers 304. For example, as shown in FIG. 8, the identifiercapture device 708 includes an imaging device 800 and one or more lightsources 802 (e.g., a flash source). In implementations, the imagingdevice 800 includes a camera or other optical detector configured tocapture, image, or otherwise recognize the sample identifier 302 whilethe imaging device 800 is moving, stationary, or both. For example, theimaging device 800 can capture video images of the sample identifiers302 and surrounding areas, such that the imaging device 800 can beassociated with a display for displaying the captured images, such as ona live or continuous basis. Alternatively or additionally, the imagingdevice 800 is configured to provide still images of a target, such asthe sample identifiers 302. The light source 802 may be configured toilluminate the bottom of the sample containers 304 and/or the sampleholders 600 such that the sample identifier 302 has increased visibilityto the imaging device 800 during imaging of the sample identifier 302.In an implementation, the identifier capture device 708 is aided by anexternal light source 804 to provide illumination in addition to orinstead of the light source 802. For example, the external light source804 can be mounted on the identifier arm assembly 710.

Sample Container Discovery

In implementations, the sample preparation system 108 executes adiscovery operation to introduce data to the system 100 regarding thepositions and identities of samples in the specific rack and vial slotsof the sample preparation system 108. An example discovery operation isdescribed with respect to FIGS. 9A and 9B, where six sample containers304 are held by a first sample holder 600A in positions 1 through 6,respectively. The identifier capture device 708 of the samplepreparation system 108 scans the unique sample identifiers 302positioned on the sample containers 304, where rack/holder and vialinformation is transmitted to the sample analysis information system 102for association with the samples identified according to the uniquesample identifiers 302. For example, the identifier capture device 708travels below the raised surface 712 to scan each unique sampleidentifier 302 positioned on a bottom surface of each sample container304 through control of the positioning of the identifier capture device708 along the center slot 706 and the rotation of the identifier capturedevice 708 by the support 602 and the identifier arm assembly 710. Inimplementations, the rack/holder and vial information is based on thepositioning of the support 602 within the center slot 706 and theposition or rotation of the identifier capture device 708 (e.g.,relative to an indexing point, relative to the raised surface 712,etc.). For example, when the system 100 identifies the identifiercapture device 708 as being positioned under the first sample holder600A at position 1 (e.g., based on translation and/or rotation from anindexing point), the system 100 can enter rack/holder and vialinformation to the sample analysis information system 102 attributableto the first sample holder 600A at position 1 as opposed to a secondsample holder 600B on an opposite side of the center slot 716 on theraised surface 712 or a different position at the first sample holder600A.

FIG. 9B shows an example distribution of the sample types held in thefirst sample holder 600A following the discovery operation. Thediscovery operation performed by the sample preparation system 108 canresult in identification of the specific sample identities present atthe specific positions within the sample holders 600 based on the uniquesample identifiers 302. For instance, the system 100 can retrieve sampletype information and other data associated with the unique sampleidentifiers 302 as entered through the sample logging manager 106. Forexample, the system 100 identifies sample identifiers 302 associatedwith an ultrapure water (UPW) sample type present in positions 3 and 5of the first sample holder 600A, sample identifiers 302 associated witha hydrogen peroxide (H₂O₂) sample type present in positions 1 and 4, andsample identifiers 302 associated with a sulfuric acid (H₂SO₄) sampletype present in positions 2 and 6. In implementations, the samplepreparation system 108 moves the identifier capture device 708 along thepositions of the sample containers 304 in a serial manner, howevernon-serial scanning methods are also contemplated (e.g., tracking of theidentifier capture device 708 during scanning to account for positioningduring non-serial scanning). In implementations, if no sample identifier302 is detected in a predefined number of positions of a sample holder(e.g., within one position, within two positions, within threepositions, etc.), the sample preparation system 108 directs theidentifier capture device 708 to a different sample holder to scan forsample identifiers 302. For instance, if the first two positions of asample rack 600 are empty, then the sample preparation system 108 skipsthe remainder of the positions of the sample rack 600, proceeding asthough they are empty to perform a faster discovery operation than ifthe identifier capture device 708 is passed by every position of asample rack when no sample identifiers 302 are discovered.

Sample Queue Preparation

Following discovery, the system 100 can automatically queue samples forsample preparation and analysis, including introducing fluids to thesample container (e.g., offline or inline), moving sample from onesample container to one or more sample containers (e.g., to providereplicates, archivable samples, etc.), introducing standards atdiffering dilution factors to build calibration curves for the samples,introducing a wash procedure between different sample types, and thelike, based on the information associated with sample types input viathe sample data manager 104. For example, the system 100 can queue theidentified samples based on the associated sample orders assigned to thesample types of the samples entered via the sample logging manager 106.In implementations, samples having the same sample type are processedsequentially before samples having different sample types. For example,all samples having a sample type of hydrogen fluoride would be processedbefore samples having a sample type of hydrogen peroxide (based on theprevious example of sample order of 1 for hydrogen fluoride and sampleorder of 2 for hydrogen peroxide). As such, the processing of samplesdoes not require the serial arrangement of samples within the sampleholder 600, where the queue can generate a non-serial distribution ofsample containers to process. In the example sample configuration ofFIG. 9B, the UPW sample type samples would be processed first (e.g.,first the sample container at position 3, then the sample container atposition 5), then the H₂O₂ samples (e.g., first the sample container atposition 1, then the sample container at position 4), and then the H₂SO₄samples (e.g., first the sample container at position 2, then the samplecontainer at position 6) in an instance where the priority of sampleorder assigned by the sample data manager 104 indicates a sample typepriority for UPW, then a priority of H₂O₂, and then a priority of H₂SO₄.The queue includes preparing and analyzing standards for each sampletype at varying concentrations to build a calibration curve specific tothe sample type for the sample based on the calibration information(e.g., calibration type, number of calibration points, dilution factorfor each calibration point, etc.) entered for the sample type via thesample data manager 104.

In implementations, the queue also includes introducing a wash procedure(e.g., to introduce a wash fluid through the fluid lines of the samplepreparation system 108, the sample analysis system 110, or combinationsthereof) after all samples of a given sample type are processed. Forinstance, in the example sample configuration of FIG. 9B, a first washprocedure is scheduled after the samples in positions 3 and 5 have bothbeen processed (e.g., including the corresponding standards used tobuild the respective calibration curves), a second wash procedure isscheduled after the samples in positions 1 and 4 have both beenprocessed, and a third wash procedure is scheduled after the samples inpositions 2 and 6 have both been processed. Differing wash procedurescan introduce different fluids, have different wash volumes or flowrates, or the like, through valve and pump control of the samplepreparation system 108 upon execution of the wash procedure of thesample type protocol.

The discovery operation facilitates discovery of the sample types andtheir specific rack/vial locations regardless of positioning at thesample preparation system 108. As such, the sample preparation system108 processes samples according to the identified sample types at theirspecific rack/vial locations as opposed to being reliant on a serialdistribution of samples at the container holder 600. Accordingly, thesystem 100 coordinates the proper order and sample type protocol foreach sample automatically, and without need for the individual placingthe samples at the sample preparation system 108 to place the samples ina specific arrangement and without need for the individual to enter asample type protocol for the samples. In implementations, a manual entryfeature is provided for a user to manually enter a sample present at thesample preparation system 108 and associate a sample type with thatsample, such as for samples not previously entered into the samplelogging manager 106 (e.g., due to scanner malfunction or otherwise). Inimplementations, the sample data manager 104 can provide a real-timeview of the sample queue as determined by the system 100. An exampleuser interface of the sample data manager 104 showing the sample queueis shown with reference to FIG. 10.

As the samples and associated standards are prepared by the samplepreparation system 108, they are transferred to the sample analysissystem 110 for analytic determination of the contents thereof. Theresults of the analytic determinations are provided to the sampleanalysis information system 102, where they are available for review viathe sample data manager 104 or other access terminal. Inimplementations, the results of operation of the sample analysis system110 are provided to the sample analysis information system 102 inreal-time. An example user interface of the sample data manager 104showing example concentration data of various elements is shown withreference to FIG. 11.

Example Methods for Managing Sample Preparation and Analysis

Referring now to FIG. 12, a flow diagram of a method 1200 for managingdata associated with sample preparation and analysis is shown inaccordance with example implementations of the present disclosure. Themethod 1200 includes storing a sample type and a sample type protocolvia a sample data manager in block 1202. For example, a user withmodification authority (e.g., a lab manager) can enter data associatedwith the sample type and sample type protocol via the sample datamanager 104 for storage on the sample analysis information system 102,where the sample type protocol becomes available for execution by thesample preparation system 108. The sample data manager 104 thusfacilitates adding or modifying specific sample type protocols forautomatic execution by the sample preparation system 108, which canensure that consistent protocols are utilized by the system 100 toprepare samples for analysis by the sample analysis system 110. Themethod 1200 also includes storing an association between a uniqueidentifier positioned on a sample container and the sample type via asample logging manager in block 1204. For example, a user (e.g., a labtechnician) can scan a sample identifier 302 on a sample container 304with the bar code scanner 300 and select via the sample logging manager106 a sample type (established via the sample data manager 104) toassociate the sample type with the specific sample container 304 andcorresponding sample identifier 302.

The method 1200 also includes identifying the unique identifier with anidentifier capture device of a sample preparation system in block 1206.For example, the sample preparation system 108 scans the sampleidentifiers 302 on the sample containers 304 with the identifier capturedevice 708 to identify the unique locations of the sample containers 304and their corresponding sample identifiers 302 held at the samplepreparation system 108 in sample holders 600. The method 1200 alsoincludes accessing the sample type protocol based on the sample typeassociated with the unique identifier in block 1208. For example, one ormore of the sample analysis information system 102, the sample datamanager 104, the sample preparation system 108, or other portion ofsystem 100 can access the sample type protocol established by the sampledata manager 104 for the unique identifier 302 identified by the samplepreparation system 108 based on the sample type assigned to the uniqueidentifier 302 via the sample logging manager 106. The method 1200 alsoincludes queuing a sampling procedure to execute the sample typeprotocol based on a sample order assigned to the sample type via thesample data manager in block 1210. For example, one or more of thesample analysis information system 102, the sample data manager 104, thesample preparation system 108, or other portion of system 100 canexecute the sample type protocol established via the sample data manager104 for each sample identified at the sample preparation system 108based on a sample order assigned to the particular sample type via thesample data manager 104. The sample type protocol can include, forexample, preparing and analyzing a plurality of standard solutions tobuild a calibration curve for each sample, executing a washing procedurefollowing completion of analysis of a group of the same sample typespresent at the sample preparation system 108, and the like.

Referring now to FIG. 13, a flow diagram of a method 1300 for managingdata associated with sample preparation and analysis is shown inaccordance with example implementations of the present disclosure. Themethod 1300 includes storing a sample type and a sample type protocolvia a sample data manager in block 1302. For example, a user withmodification authority (e.g., a lab manager) can enter data associatedwith the sample type and sample type protocol via the sample datamanager 104 for storage on the sample analysis information system 102,where the sample type protocol becomes available for execution by thesample preparation system 108. The sample data manager 104 thusfacilitates adding or modifying specific sample type protocols forautomatic execution by the sample preparation system 108, which canensure that consistent protocols are utilized by the system 100 toprepare samples for analysis by the sample analysis system 110. Themethod 1200 also includes identifying a unique identifier positioned ona sample container with an identifier capture device of the samplepreparation system in block 1304. For example, the sample preparationsystem 108 scans the sample identifiers 302 on the sample containers 304(e.g., with the identifier capture device 708, with a scanner of themass balance 500, etc.) to identify sample present at the samplepreparation system 108, or a lack of identified samples present at thesample preparation system 108.

The method 1300 also includes storing an association between the uniqueidentifier positioned on the sample container and the sample type via asample logging manager in block 1306. For example, a user (e.g., a labtechnician) can scan a sample identifier 302 on a sample container 304(e.g., with the bar code scanner 300, with the identifier capture device708, with a scanner of the mass balance 500, etc.) and select via thesample logging manager 106 a sample type (established via the sampledata manager 104) to associate the sample type with the specific samplecontainer 304 and corresponding sample identifier 302.

The method 1300 also includes accessing the sample type protocol basedon the sample type associated with the unique identifier in block 1308.For example, one or more of the sample analysis information system 102,the sample data manager 104, the sample preparation system 108, or otherportion of system 100 can access the sample type protocol established bythe sample data manager 104 for the unique identifier 302 identified bythe sample preparation system 108 based on the sample type assigned tothe unique identifier 302 via the sample logging manager 106. The method1300 also includes executing the sample type protocol via the samplepreparation system in block 1310. For example, the sample preparationsystem 108 can execute the sample type protocol accessed via the sampleanalysis information system and established via the sample data manager104 for each sample identified at the sample preparation system 108 toprepare samples for analysis or facilitate their preparation for futureanalysis. The sample type protocol can include, for example, introducingfluids to the sample container (e.g., offline or inline), moving samplefrom one sample container to one or more sample containers (e.g., toprovide replicates, archivable samples, etc.), introducing standards atdiffering dilution factors to build calibration curves for the samples,introducing a wash procedure between different sample types, and thelike, based on the information associated with sample types input viathe sample data manager 104.

Sample Container Status Tracking

The system 100 can also facilitate tracking of sample containers 304through a facility or group of facilities. The unique identifiers 302 onthe sample containers 304 can be used to track data associated with eachsample container 304 through scanning of the unique identifiers (e.g.,via the bar code scanner 300 or other device) during various portions ofthe cycle of use of the sample container and storage and access of thedata via the sample analysis information system 102 or other portion ofthe system 100. For instance, the data associated with each samplecontainer 304 can include, but is not limited to, a current status ofthe sample container, a location of the sample container, a sample typecurrently held in the sample container, a concentration of analytecurrently held in the sample container, a history of samples types heldin the sample container, a history of concentration of analytes held inthe sample container, and the like.

The status of a sample container 304 is dependent on the particularportion of the cycle of use of the sample container 304 and can include,but is not limited to, an available status, a carry out status, areceiving status, an analysis status, a completed status, a cleaningstatus, and a verification status. The available status can refer to asample container 304 being stored in a cleaned state, ready to be usedfor holding a sample. For example, a user can utilize the sample loggingmanager 106 and the bar code scanner 300 or other device to scan thesample identifier 302 of the sample container 304 and input theavailable status to be associated with the particular sample identifier302 (e.g., stored at the sample analysis information system 102). Inimplementations, the sample container statuses available for selectionvia the sample logging manager 106 are input into the system 100 via thesample data manager 104 interface.

The carry out status can refer to removal of the sample container 304from storage for collection of a particular sample in the samplecontainer 304. For example, a user can utilize the sample loggingmanager 106 and the bar code scanner 300 or other device to scan thesample identifier 302 of the sample container 304 and input the carryout status to be associated with the particular sample identifier 302following removal from storage. Once a sample is introduced to thesample container 304, a user can transfer the sample container 304 to alaboratory or other location for analysis of the sample. The receivingstatus can refer to receipt of the sample container 304 in thelaboratory or other location, prior to analysis of the sample held inthe sample container 304 (e.g., the sample is awaiting analysis). Forexample, a user can utilize the sample logging manager 106 and the barcode scanner 300 or other device to scan the sample identifier 302 ofthe sample container 304 and input the receiving status to be associatedwith the particular sample identifier 302 following transfer of thesample container 304 to the laboratory or other location for analysis.

The analysis status can refer to processing of the sample for analysis.For example, the sample preparation system 108 can scan the sampleidentifier 302 (e.g., during the discovery operation described herein)and upload the analysis status to the sample analysis information system102. Alternatively or additionally, a user can utilize the samplelogging manager 106 and the bar code scanner 300 or other device to scanthe sample identifier 302 of the sample container 304 while placing thesample container at the sample preparation device 108 (e.g., in thesample holder 600). The completed status can refer to analysis of thesample by the sample analysis system 110 being complete. For example,the sample analysis system 110 can upload the completed status to thesample analysis information system 102 once concentration data of theanalytes of interest of the sample are provided to the sample analysisinformation system 102, the sample data manager 104, or other portion ofsystem 100.

The cleaning status can refer to washing the sample container 304 toremove residual contaminants or residual sample following analysis ofthe sample. For example, a user can utilize the sample logging manager106 and the bar code scanner 300 or other device to scan the sampleidentifier 302 of the sample container 304 and input the cleaning statusto be associated with the particular sample identifier 302 followinganalysis of the sample from the sample container 304. Additionally oralternatively, a wash station can include a bar code scanner 300, anidentifier capture device 708, or other scanning device to automaticallyscan the sample identifier 302 when received for cleaning, duringcleaning, following cleaning, or the like, to associate the cleaningstatus with the sample identifier 302 for access at the sample analysisinformation system 102. Following cleaning, a sample container 304 canbe introduced to storage, where the sample identifier 302 can beassociated with the available status, or the sample container 304 can betransferred to a sample preparation system 108 to prepare a sample fromthe sample container 304 for analysis by the sample analysis system 110to analytically verify the cleanliness of the sample container 304. Forexample, the sample preparation system 108 can scan the sampleidentifier 302 (e.g., during the discovery operation described herein)and upload the verification status to the sample analysis informationsystem 102. Alternatively or additionally, a user can utilize the samplelogging manager 106 and the bar code scanner 300 or other device to scanthe sample identifier 302 of the sample container 304 while placing thesample container at the sample preparation device 108 (e.g., in thesample holder 600) for verification.

Computer System Implementation

Aspects of the system 100 described herein are executed in a computersystem. For example, one or more components of the sample analysisinformation system 102, the sample data manager 104, the sample loggingmanager 106, the sample preparation system 108, and the sample analysissystem 110 include a computing device, communicate with a computingdevice through a network, or both, to facilitate aspects of thedisclosure described herein. For example, one or more components of thesample analysis information system 102, the sample data manager 104, thesample logging manager 106, the sample preparation system 108, and thesample analysis system 110 can include a computer controller or areoperably coupled with a computer controller to execute the operationsdescribed herein. For example, the system 100 can include a computingdevice having a processor and memory or communicatively coupled with aprocessor and/or memory. The processor provides processing functionalityfor the computing device and may include any number of processors,micro-controllers, or other processing systems, and resident or externalmemory for storing data and other information accessed or generated bythe computing device. The processor may execute one or more softwareprograms that implement the techniques described herein. The processoris not limited by the materials from which it is formed or theprocessing mechanisms employed therein and, as such, may be implementedvia semiconductor(s) and/or transistors (e.g., electronic integratedcircuits (ICs)), and so forth.

Memory accessible by the controller is an example of device-readablestorage media that provides storage functionality to store various dataassociated with the operation of the computing device, such as softwareprograms or code segments, or other data to instruct the processor andother elements of the computing device to perform the techniquesdescribed herein. A wide variety of types and combinations of memory maybe employed. The memory may be integral with the processor, stand-alonememory, or a combination of both. The memory may include, for example,removable and non-removable memory elements such as RAM, ROM, Flash(e.g., SD Card, mini-SD card, micro-SD Card), magnetic, optical, USBmemory devices, and so forth. In embodiments of the computing device,the memory may include removable ICC (Integrated Circuit Card) memorysuch as provided by SIM (Subscriber Identity Module) cards, USIM(Universal Subscriber Identity Module) cards, UICC (Universal IntegratedCircuit Cards), and so on.

The computing device includes a display to display information to a userof the computing device. In embodiments, the display may comprise a CRT(Cathode Ray Tube) display, an LED (Light Emitting Diode) display, anOLED (Organic LED) display, an LCD (Liquid Crystal Diode) display, a TFT(Thin Film Transistor) LCD display, an LEP (Light Emitting Polymer) orPLED (Polymer Light Emitting Diode) display, and so forth, configured todisplay text and/or graphical information such as a graphical userinterface. The display may be backlit via a backlight such that it maybe viewed in the dark or other low-light environments. The display maybe provided with a touch screen to receive input (e.g., data, commands,etc.) from a user. For example, a user may operate the computing deviceby touching the touch screen and/or by performing gestures on the touchscreen. In some embodiments, the touch screen may be a capacitive touchscreen, a resistive touch screen, an infrared touch screen, combinationsthereof, and the like. The computing device may further include one ormore input/output (I/O) devices (e.g., a keypad, buttons, a wirelessinput device, a thumbwheel input device, a trackstick input device, andso on). The I/O devices may include one or more audio I/O devices, suchas a microphone, speakers, and so on. The user interface may providefunctionality to allow the user to interact with one or moreapplications of the computing device by providing inputs (e.g., sampleidentities, sample locations, sample type protocols, sample rack type,fluid flow rates, analysis system operation, valve timing, pump timing,etc.) via the touch screen and/or the I/O devices. For example, the userinterface may cause an application programming interface (API) to begenerated to expose functionality to a sample analysis informationsystem controller to allow the user to interact with an application byproviding inputs via the touch screen and/or the I/O devices to providedesired sample throughput or sample preparation and subsequent analysis.

The computing system may also include a communication interface totransfer of data or control instructions between different devices(e.g., components/peripherals) and/or over one or more networks. Thecommunication interface may include a variety of communicationcomponents and functionality including, but not necessarily limited to:a browser; a transmitter and/or receiver; data ports; softwareinterfaces and drivers; networking interfaces; data processingcomponents; and so forth.

The one or more networks are representative of a variety of differentcommunication pathways and network connections which may be employed,individually or in combinations, to communicate among the components ofthe system 100. Thus, the one or more networks may be representative ofcommunication pathways achieved using a single network or multiplenetworks. Further, the one or more networks are representative of avariety of different types of networks and connections that arecontemplated including, but not necessarily limited to: the Internet; anintranet; a Personal Area Network (PAN); a Local Area Network (LAN)(e.g., Ethernet); a Wide Area Network (WAN); a satellite network; acellular network; a mobile data network; wired and/or wirelessconnections; and so forth. Examples of wireless networks include, butare not necessarily limited to: networks configured for communicationsaccording to: one or more standard of the Institute of Electrical andElectronics Engineers (IEEE), such as 802.11 or 802.16 (Wi-Max)standards; Wi-Fi standards promulgated by the Wi-Fi Alliance; Bluetoothstandards promulgated by the Bluetooth Special Interest Group; and soon. Wired communications are also contemplated such as through UniversalSerial Bus (USB), Ethernet, serial connections, and so forth.

Although particular embodiments of this invention have been illustrated,it is apparent that various modifications and embodiments of theinvention may be made by those skilled in the art without departing fromthe scope and spirit of the foregoing disclosure. Accordingly, the scopeof the invention should be limited only by the claims appended hereto.

While the subject matter has been described in language specific tostructural features and/or process operations, it is to be understoodthat the subject matter defined in the appended claims is notnecessarily limited to the specific features or acts described above.Rather, the specific features and acts described above are disclosed asexample forms of implementing the claims.

What is claimed is:
 1. A method for managing data associated with sampleanalysis comprising: storing on a sample analysis information system asample type and a sample type protocol for execution by a samplepreparation system via a sample data manager; storing on the sampleanalysis information system an association between a unique identifierpositioned on a sample container and the sample type with a samplelogging manager; identifying the unique identifier at the samplepreparation system with an identifier capture device of the samplepreparation system; accessing from the sample analysis informationsystem the sample type protocol based on the sample type associated withthe unique identifier; and queuing a sampling procedure to execute thesample type protocol based on a sample order assigned to the sample typevia the sample data manager.
 2. The method of claim 1, whereinidentifying the unique identifier at the sample preparation system withan identifier capture device of the sample preparation system includes:scanning a unique location of each sample container; and storing on thesample analysis information system an association between the uniquelocation and the unique identifier positioned on the sample containerwhere the sample container is located.
 3. The method of claim 2, whereinqueuing a sampling procedure to execute the sample type protocol basedon a sample order assigned to the sample type via the sample datamanager includes: queuing the sampling procedure to execute the sampletype protocol based on the sample order assigned to the sample type viathe sample data manager and based on the unique location associated bythe identifier capture device with the unique identifier positioned onthe sample container.
 4. The method of claim 2, wherein queuing asampling procedure to execute the sample type protocol based on a sampleorder assigned to the sample type via the sample data manager includes:preparing sample types having sample orders with a higher priority viathe sample preparation system before sample types having sample orderswith a lower priority.
 5. The method of claim 2, wherein queuing asampling procedure to execute the sample type protocol based on a sampleorder assigned to the sample type via the sample data manager includes:queuing the sampling procedure to execute the sample type protocolaccording to a non-serial distribution of unique locations of samplecontainers at the sample preparation system.
 6. The method of claim 5,wherein identifying the unique identifier at the sample preparationsystem with an identifier capture device of the sample preparationsystem includes: scanning each unique location in a serial manner toidentify any unique identifiers present at each unique location.
 7. Themethod of claim 1, wherein the sample type protocol includes dataassociated with at least one of a dilution factor specific to the sampletype, a calibration type specific to the sample type, a number ofcalibration points specific to the sample type, and a dilution factorassociated with a calibration point specific to the sample type.
 8. Themethod of claim 1, further comprising: transferring a sample from thesample preparation system to a sample analysis system communicativelyconnected with the sample analysis information system; and determining aconcentration of one or more analytes of interest in the sample via thesample analysis system.
 9. The method of claim 8, wherein the sampletype protocol includes an analysis protocol accessible by the sampleanalysis system, wherein the analysis protocol includes at least one ofa list of analytes to be analyzed by the sample analysis system,calibration levels for each standard calibration for each analyte to beanalyzed by the sample analysis system, and dilution factors for eachstandard calibration for each analyte to be analyzed by the sampleanalysis system.
 10. The method of claim 1, further comprising: storingon the sample analysis information system data associated with thesample container based on the unique identifier.
 11. The method of claim10, wherein the data associated with the sample container includes atleast one of a current status of the sample container, a location of thesample container, a sample type currently held in the sample container,a concentration of analyte currently held in the sample container, ahistory of samples types held in the sample container, and a history ofconcentration of analytes held in the sample container.
 12. Anon-transitory computer readable medium having stored thereoninstructions that, when executed by a processor, cause the processor togenerate control signals for controlling a sample preparation system, byexecuting the steps comprising: storing on a sample analysis informationsystem a sample type and a sample type protocol for execution by asample preparation system via a sample data manager; storing on thesample analysis information system an association between a uniqueidentifier positioned on a sample container and the sample type with asample logging manager; identifying the unique identifier at the samplepreparation system with an identifier capture device of the samplepreparation system; accessing from the sample analysis informationsystem the sample type protocol based on the sample type associated withthe unique identifier; and queuing a sampling procedure to execute thesample type protocol based on a sample order assigned to the sample typevia the sample data manager.
 13. A method for managing data associatedwith sample analysis comprising: storing on a sample analysisinformation system a sample type and a sample type protocol forexecution by a sample preparation system via a sample data manager;identifying a unique identifier positioned on a sample container at thesample preparation system with an identifier capture device of thesample preparation system; storing on the sample analysis informationsystem an association between the unique identifier and the sample typewith a sample logging manager; accessing from the sample analysisinformation system the sample type protocol based on the sample typeassociated with the unique identifier; and executing the sample typeprotocol via the sample preparation system.
 14. The method of claim 13,wherein the sample preparation system includes a mass balance configuredto measure a weight of sample held within the sample container.
 15. Themethod of claim 14, wherein the sample type protocol includes a minimumweight of sample and a maximum weight of sample.
 16. The method of claim15, further comprising: displaying a current weight of sample held onthe mass balance on the display in a first format when the currentweight is below the minimum weight of sample or above the maximum weightof sample; and displaying the current weight of sample held on the massbalance on the display in a second format when the current weight is atthe minimum weight of sample, between the minimum weight of sample andthe maximum weight of sample, or at the maximum weight of sample,responsive to execution of the sample type protocol.
 17. The method ofclaim 14, wherein the mass balance includes a scanner configured toidentify the unique identifier positioned on the sample container. 18.The method of claim 13, further comprising one or more of: transferring,via a sample probe, sample from the sample container to one or moreadditional sample containers responsive to execution of the sample typeprotocol; and introducing, via the sample probe, one or more additionalfluids to the sample container responsive to execution of the sampletype protocol.
 19. The method of claim 13, further comprising:transferring, via a sample probe, sample from the sample container toone or more additional sample containers responsive to execution of thesample type protocol; and introducing, via the sample probe, one or moreadditional fluids to the one or more additional sample containersresponsive to execution of the sample type protocol.
 20. The method ofclaim 13, wherein identifying the unique identifier at the samplepreparation system with an identifier capture device of the samplepreparation system includes: scanning a unique location of each samplecontainer; and storing on the sample analysis information system anassociation between the unique location and the unique identifierpositioned on the sample container where the sample container islocated.
 21. A non-transitory computer readable medium having storedthereon instructions that, when executed by a processor, cause theprocessor to generate control signals for controlling a samplepreparation system, by executing the steps comprising: storing on asample analysis information system a sample type and a sample typeprotocol for execution by a sample preparation system via a sample datamanager; identifying a unique identifier positioned on a samplecontainer at the sample preparation system with an identifier capturedevice of the sample preparation system; storing on the sample analysisinformation system an association between the unique identifier and thesample type with a sample logging manager; accessing from the sampleanalysis information system the sample type protocol based on the sampletype associated with the unique identifier; and executing the sampletype protocol via the sample preparation system.